On Failure Of Ai Projects

Why is this study made?

• Westenberger, Schuler, and Schlegel (2022) wrote a paper that explores the critical factors that contribute to AI project failure.
• Some studies have been conducted on the critical factors of IS project success and failure; however, there is no study yet that focuses on AI projects.
• They interviewed 6 respondents to bucket the factors into the following:
  • Unrealistic expectations
  • Use case related issues
  • Organizational constraints
  • Lack of key resources
  • Technological issues
• The study concludes that “there are several technological and non-technological factors that can lead to success or failure of AI projects” (Westenberger et al., 2022).

Who is this study for?

• The respondents of the study belong to top, middle, and low level of management hierarchy.
• This study appears to be made for different stakeholders.

What is useful in this study?

• Factors under unrealistic expectations are “misunderstanding of AI capabilities” and “thinking too big” related to language and culture.
• This implies the importance of establish shared language and culture in the organization to make AI projects successful.

What if?

• What if we increase this size? Will the conclusion still hold?

Reference

• Westenberger, J., Schuler, K., & Schlegel, D. (2022). Failure of AI projects: Understanding the critical factors. Procedia Computer Science, 196, 69–76. https://doi.org/10.1016/j.procs.2021.11.074

Related Literature

• Creating Shared Value